Security Scan Report: uninterested-pink-jksus937jj-i4c4yfxnap.edgeone.app

Submitted: Feb 24, 2026, 12:29:28 AMCompleted: Feb 24, 2026, 12:30:37 AMpubliccompleted
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Summary

This website contacted 3 IPs in 1 country across 3 domains to perform 1 HTTP transaction. The main domain is uninterested-pink-jksus937jj-i4c4yfxnap.edgeone.app and was registered NaN years ago.

Submitted URL: https://uninterested-pink-jksus937jj-i4c4yfxnap.edgeone.app/

The Cisco Umbrella rank of the primary domain is #455,732 of the top 1 million websites

AI Security Verdict

Moderate Risk

Confidence: 68%

4
Risk Score

Personal portfolio on a new free‑hosting subdomain; no malicious indicators detected.

Safety Factors
No credential or payment collection fields
No malicious JavaScript or YARA detections
No cross‑origin credential exfiltration observed
Content appears to be a personal legal portfolio
Domain age information unavailable

Details

Page Title

Rifki Pebrianto — Legal Portfolio

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government public service

(70%)

Domain Information

The domain 'uninterested-pink-jksus937jj-i4c4yfxnap.edgeone.app' uses the application-focused generic top-level domain (.app); it also runs on subdomain 'uninterested-pink-jksus937jj-i4c4yfxnap'. The second-level label 'edgeone' is 7 characters long containing four vowels alongside three consonants. Splitting it apart reveals two words: edge, one. Median word length comes out to 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://uninterested-pink-jksus937jj-i4c4yfxnap.edgeone.app/

Page Load Overview

0.68s
Total Load Time
12
HTTP Requests
3
Domains
300 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:4,540 chars
Detector Agreement:67%

Website Classification

Primary Category

government public service70% confidence
Type: static
Method: ml+structural

All Detected Categories

government public service
70%
adult content
65%
education learning
48%
blog personal website
28%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
443.152.26.58Singapore
4216.58.206.67Singapore
4172.217.20.138SingaporeUnknown
123--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T15003D725B6721126A12392D037D7131E33B4E103E5464938B3FE4A85CFCDDE4EA939AE

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:hwOiaBxRgh9JJVUPqy10eMnawdvjWB73PK0dy9CnL82LKeLXBL8pLg+EY2QXSTFo:hiaBfgh9JJVUPqy10eMnawdvjWB73PKZ

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:40719:EAJgAsGQWMRgAJ7MwMTACdIKBmTYGhZsPuZUDUyAgQiqEAhKAIDQQDkIBY6wFgINAWcAAQFGiSMUzAQCIbiBQBA22YGRIRO0

These hashes enable detection of similar websites and malware variants by comparing content similarity even when exact matches aren't found.

Image Hashes

Perceptual Hashes

Average Hash:030383cfcf818181
Perceptual Hash:baa50701f0fe3f03
Difference Hash:07873f3b99292101
Wavelet Hash:070387cfcfcfc181
Color Hash:#9ae06c

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data